Selected Publications

• Staerk, C., Klinkhammer, H., Wistuba, T., May, C., & Mayr, A. (2024). Generalizability of polygenic prediction models: how is the R2 defined on test data? BMC Medical Genomics, 17(132). [Paper] 

• Staerk, C., Byrd, A., & Mayr, A. (2024). Recent methodological trends in Epidemiology: No need for data-driven variable selection? American Journal of Epidemiology, 193(2), 370-376. [Preprint; Web Material; Paper] 

• Staerk, C., Kateri, M., & Ntzoufras, I. (2024). A Metropolized adaptive subspace algorithm for high-dimensional Bayesian variable selection. Bayesian Analysis, 19(1), 261-291.  [Paper; Code]

• Strömer, A., Klein, N., Staerk, C., Klinkhammer, H., & Mayr, A. (2023). Boosting multivariate structured additive distributional regression models. Statistics in Medicine, 1-23. [Paper; Code]

• Klinkhammer, H., Staerk, C., Maj, C., Krawitz, P. M., & Mayr, A. (2023). A statistical boosting framework for polygenic risk scores based on large-scale genotype data. Frontiers in Genetics, 13(1076440). [Paper; Code]

• Wistuba, T., Mayr, A., & Staerk, C. (2022). Estimating the course of the COVID-19 pandemic in Germany via spline-based hierarchical modelling of death counts. Scientific Reports, 12(9784). [Paper; Code]

• Maj, C.*, Staerk, C.*, Borisov, O., Klinkhammer, H., Yeung, M. W., Krawitz, P., & Mayr, A. (2022). Statistical learning for sparser fine-mapped polygenic models: The prediction of LDL-cholesterol. Genetic Epidemiology. [Paper, *contributed equally] 

• Hilbert, A., Staerk, C., Strömer, A., Mansfeld, T., Sander, J., Seyfried, F., Kaiser, S., Dietrich, A., & Mayr, A. (2022). Nonnormative eating behaviors and eating disorders and their associations with weight loss and quality of life during 6 years following obesity surgery. JAMA Network Open, 5(8), e2226244. [Paper]

• Stumpfe, F. M., Schneider, M. O., Hein, A., Faschingbauer, F., Kehl, S., Hermanek, P., Böhm, J., Scharl, A., Beckman, M. W., Staerk, C.* & Mayr, A.* (2022). Limited effects of SARS-CoV-2 pandemic-related lockdowns and reduced population mobility on preterm birth rates: A secondary analysis of Bavarian obstetric quality parameters from 2010 to 2020. Geburtshilfe und Frauenheilkunde, 82(08), 842-851. [Paper, *joint senior authors]

• Selaskowski, B., Staerk, C., Braun, N., Matthies, S., Graf, E., Colla, M., ... Mayr, A., & Philipsen, A. (2022). Multimodal treatment efficacy differs in dependence of core symptom profiles in adult Attention-Deficit/Hyperactivity Disorder: An analysis of the randomized controlled COMPAS trial. Journal of Psychiatric Research, 151, 225-234. [Preprint, Paper]

• Strömer, A., Staerk, C., Klein, N., Weinhold, L., Titze, S., & Mayr, A. (2022). Deselection of base-learners for statistical boosting—with an application to distributional regression. Statistical Methods in Medical Research, 31(2), 207-224. [Preprint; Paper; Code]

• Staerk, C., & Mayr, A. (2021). Randomized boosting with multivariable base-learners for high-dimensional variable selection and prediction. BMC Bioinformatics, 22(441). [Paper; Code]

• Staerk, C., Wistuba, T., & Mayr, A. (2021). Estimating effective infection fatality rates during the course of the COVID-19 pandemic in Germany. BMC Public Health, 21(1073). [Paper]

• Boenniger, M. M., Staerk, C., Coors, A., Huijbers, W., Ettinger, U., & Breteler, M. M. (2021). Ten German versions of Rey’s auditory verbal learning test: Age and sex effects in 4,000 adults of the Rhineland Study. Journal of Clinical and Experimental Neuropsychology, 43(6), 637-653. [Paper]

• Dürr, P., Schlichtig, K., Kelz, C., Deutsch, B., Maas, R., Eckart, M. J., Wilke J., Wagner H., Wolff K., Preuß C., Brückl V., Meidenbauer N., Staerk C., Mayr A., Fietkau R., Goebell P. J., Kunath F., Beckmann M. W., Mackensen A., Neurath M. F., Pavel M., Dörje F., & Fromm, M. F. (2021). The randomized AMBORA trial: Impact of pharmacological/pharmaceutical care on medication safety and patient-reported outcomes during treatment with new oral anticancer agents. Journal of Clinical Oncology, 39(18), 1983-1994. [Paper]

• Staerk, C., Kateri, M., & Ntzoufras, I. (2021). High-dimensional variable selection via low-dimensional adaptive learning. Electronic Journal of Statistics, 15(1), 830-879. [Paper; Code]

For the full list of publications see Google Scholar. 

Some Talks

• BIFI (Institute for Biocomputation and Physics of Complex Systems) International Conference, 2022, Estimating the course of the COVID-19 pandemic in Germany via spline-based hierarchical modelling of death counts. [Slides]

• 16. Jahrestagung DGEpi (Deutsche Gesellschaft für Epidemiologie), 2021, Estimating effective infection fatality rates during the course of the COVID-19 pandemic in Germany. [Slides]

PhD Thesis

Staerk., C. (2018). Adaptive subspace methods for high-dimensional variable selection. RWTH Aachen University: Fakultät für Mathematik, Informatik und Naturwissenschaften. Advisors: Maria Kateri and Ioannis Ntzoufras